Front Comput Neurosci. 2013 Nov 22;7:168. doi: 10.3389/fncom.2013.00168. eCollection 2013.
Increased motor cortex excitability during motor imagery in brain-computer interface trained subjects.
Frontiers in computational neuroscience
Olesya A Mokienko, Alexander V Chervyakov, Sofia N Kulikova, Pavel D Bobrov, Liudmila A Chernikova, Alexander A Frolov, Mikhail A Piradov
Affiliations
Affiliations
- Research Center of Neurology Russian Academy of Medical Science Moscow, Russia ; Institute of Higher Nervous Activity and Neurophysiology of RAS Moscow, Russia.
PMID: 24319425
PMCID: PMC3837244 DOI: 10.3389/fncom.2013.00168
Abstract
BACKGROUND: Motor imagery (MI) is the mental performance of movement without muscle activity. It is generally accepted that MI and motor performance have similar physiological mechanisms.
PURPOSE: To investigate the activity and excitability of cortical motor areas during MI in subjects who were previously trained with an MI-based brain-computer interface (BCI).
SUBJECTS AND METHODS: Eleven healthy volunteers without neurological impairments (mean age, 36 years; range: 24-68 years) were either trained with an MI-based BCI (BCI-trained, n = 5) or received no BCI training (n = 6, controls). Subjects imagined grasping in a blocked paradigm task with alternating rest and task periods. For evaluating the activity and excitability of cortical motor areas we used functional MRI and navigated transcranial magnetic stimulation (nTMS).
RESULTS: fMRI revealed activation in Brodmann areas 3 and 6, the cerebellum, and the thalamus during MI in all subjects. The primary motor cortex was activated only in BCI-trained subjects. The associative zones of activation were larger in non-trained subjects. During MI, motor evoked potentials recorded from two of the three targeted muscles were significantly higher only in BCI-trained subjects. The motor threshold decreased (median = 17%) during MI, which was also observed only in BCI-trained subjects.
CONCLUSION: Previous BCI training increased motor cortex excitability during MI. These data may help to improve BCI applications, including rehabilitation of patients with cerebral palsy.
Keywords: brain-computer interface; functional MRI; motor imagery; navigated TMS; neurorehabilitation
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